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Techno-economic optimal operation of the electrical distribution grid considering smart energy consumption by consumers

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Abstract

Energy optimization is one of the major issues for electrical distribution companies to meet demand with minimum generation costs and power losses. In this paper, the optimal operation of the smart electrical distribution grid is modeled by three-stage multi-objective optimization with optimal consumers’ participation and electrical storage systems (ESSs) under electrical price and load demand uncertainties at day ahead. The three strategies of demand response programs (DRPs) such as demand shifting (DS), demand curtailment (DC), and onsite generation (OG) to consumers’ participation are considered with attention to electrical price traffic. In the first and second stages, electrical demand is optimized using DS and DC strategies, respectively. Thus, optimized electrical demand is applied to the third stage optimization for minimization of the multi-objective functions including (1) minimum generation costs and (2) power losses. Also, OG is implemented by ESSs in the third stage optimization as a local resource. All stages of the proposed approach are optimized by the shuffled frog leaping (SFL) algorithm. On the other side, the TOPSIS decision-making method is used to choose the best trade-off solution in the third stage optimization. Eventually, the proposed optimization by the numerical simulation is carried out considering four case studies in IEEE 33-bus test system to demonstrate validation of the strategies. The case studies are implemented based on the participation of the consumers by using DS, DC, and OG strategies. In the first case study, the participation of the consumers is not considered, and this case is assumed as a base case study. The participation of the consumers with the DS strategy is implemented in the second case study. The DS and DC strategies are used by consumers in the third case study, simultaneously. In the fourth case study, OG with DS and DC strategies is considered for optimal participation in energy optimization. The participation of all strategies by consumers leads to minimizing energy generation costs and power loss by 5.52% and 14.68% in comparison with non-participation of the consumers.

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Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

DC:

Demand curtailment

DRPs:

Demand response programs

DG:

Diesel generator

DS:

Demand shifting

ESS:

Electrical storage system

TOPSIS:

Technique for order of preference by similarity to ideal solution

OG:

Onsite generation

\(t,T\) :

Time index

\(d,D\) :

Diesel generator (DG) index

\({\text{DS}},{\text{DS}}\) :

Index of consumers with demand shifting (DS) strategy

\({\text{dc}},{\text{DC}}\) :

Index of consumers with demand curtailing (DC) strategy

\({{\text{OG}}},{{\text{OG}}}\) :

Index of the consumers with onsite generation (OG) strategy

\({{\text{EM}}}\) :

Electrical market index

\(i,j,\Lambda\) :

Bus indices

\(s,S\) :

Scenario indices

\(\alpha ,\beta ,\lambda\) :

Fuel cost factors of DGs

\(\pi_{{{\text{EP}}}}\) :

Electrical price in electrical market

\({\text{ED}}_{{{\text{DS}}}}\) :

Active power demand of the consumers with demand shifting (DS) strategy

\({\text{ED}}_{{{\text{DC}}}}\) :

Active power demand of the consumers with demand curtailing (DC) strategy

\({\text{ED}}_{{{{\text{OG}}}}}\) :

Active power demand of the consumers with onsite generation (OG) strategy

\({\text{ED}}_{{{\text{DS}}}}^{{{\text{OP}}}}\) :

Optimized active power demand of the consumers with demand shifting (DS) strategy

\({\text{ED}}_{{{\text{DC}}}}^{{{\text{OP}}}}\) :

Optimized active power demand of the consumers with demand curtailing (DC) strategy

\({\text{QD}}_{{{\text{DS}}}}^{{{\text{OP}}}}\) :

Optimized reactive power demand of the consumers with demand shifting (DS) strategy

\({\text{QD}}_{{{\text{DC}}}}^{{{\text{OP}}}}\) :

Optimized reactive power demand of the consumers with demand curtailing (DC) strategy

\({\text{QD}}_{{{{\text{OG}}}}}\) :

Reactive power demand of the consumers with onsite generation (OG) strategy

\(\Upsilon_{{{\text{DS}}}}\) :

Participation rate of the consumers with demand shifting (DS) strategy

\(\Upsilon_{{{\text{DC}}}}\) :

Participation rate of the consumers with demand curtailing (DC) strategy

\(P_{{{{\text{OG}}}}}^{{r,{{\text{ess}}}}}\) :

Power rate of the ESS for consumers with onsite generation (OG) strategy

\({\text{RU}},{\text{RD}}\) :

Ramp up and ramp down of DGs

\(\eta^{dch} ,\eta^{ch}\) :

Efficiency of ESS in discharge and charge modes, respectively

\(r_{\Lambda }\) :

Resistance of the branch between buses i and j

\(C_{d}\) :

Generation cost of DGs

\(C_{{{{\text{EM}}}}}\) :

Generation cost of the electrical market

\({\text{ED}}_{{{\text{DS}}}} (s,t,t^{^{\prime}} )\) :

Amount of the electrical demand shifted by consumers with demand shifting (DS) strategy

\(P_{d}\) :

Active power generated by DG

\(P_{{{{\text{EM}}}}}\) :

Active power generated by electrical market

\(P_{{{\text{loss}}}}\) :

Active power losses

\(Q_{d}\) :

Reactive power generated by DG

\(Q_{{{{\text{EM}}}}}\) :

Reactive power generated by electrical market

\(Q_{{{\text{loss}}}}\) :

Reactive power losses

\(P_{\Lambda }\) :

Active power flow between buses i and j

\(Q_{\Lambda }\) :

Reactive power flow between buses i and j

\(V_{\Lambda }\) :

Voltage value in buses i and j

\(P_{{{{\text{OG}}}}}^{{ch,{{\text{ess}}}}}\) :

Power charged by ESS in onsite generation (OG) strategy

\(P_{{{{\text{OG}}}}}^{{dch,{{\text{ess}}}}}\) :

Power discharged by ESS in onsite generation (OG) strategy

\(\Omega_{{{{\text{OG}}}}}\) :

Available energy of ESS in onsite generation (OG) strategy

\(u_{{{{\text{OG}}}}}\) :

Binary variable of the ESS in onsite generation (OG) program (1 = discharge mode and 0 = Otherwise)

\(\rho_{s}^{{}}\) :

Probability of scenario s

\(\rho_{s}^{L,\Theta }\) :

Probability of load demand and electrical price in scenario s

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Authors and Affiliations

  1. Department of Electrical Engineering, Islamic Azad University, Nour Branch, Nour, Iran

    Vahid Montaghami, Mohammad Rezvani, Borzou Yousefi & Abdolreza N. Shirazi

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  1. Vahid Montaghami
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  2. Mohammad Rezvani
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  3. Borzou Yousefi
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  4. Abdolreza N. Shirazi
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All authors have equal contributions including conceptualization, methodology, software, data curation, formal analysis, writing—review and editing, and writing—original draft.

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Correspondence to Mohammad Rezvani.

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Montaghami, V., Rezvani, M., Yousefi, B. et al. Techno-economic optimal operation of the electrical distribution grid considering smart energy consumption by consumers. Electr Eng 105, 2653–2673 (2023). https://doi.org/10.1007/s00202-023-01845-z

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